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23 August 2021
What Contributes to a Crowdfunding Campaign’s Success? Evidence and Analyses from GoFundMe Data
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Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign’s success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful.
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What Contributes to a Crowdfunding Campaign’s Success? Evidence and Analyses from GoFundMe Data
)
Abstract
Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign’s success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful.
References(24)
E. Mollick, The dynamics of crowdfunding: An exploratory study, J. Bus. Ventur., vol. 29, no. 1, pp. 1–16, 2014.
A. Parhankangas and M. Renko, Linguistic style and crowdfunding success among social and commercial entrepreneurs, J. Bus. Ventur., vol. 32, no. 2, pp. 215–236, 2017.
D. Frydrych, A. J. Bock, T. Kinder, and B. Koeck, Exploring entrepreneurial legitimacy in reward-based crowdfunding, Venture Capital, vol. 16, no. 3, pp. 247–269, 2014.
M. Barbi and M. Bigelli, Crowdfunding practices in and outside the US, Res. Int. Bus. Finance, vol. 42, pp. 208–223, 2017.
Y. R. Tausczik and J. W. Pennebaker, The psychological meaning of words: LIWC and computerized text analysis methods, J. Lang. Soc. Psychol., vol. 29, no. 1, pp. 24–54, 2010.
J. Kittler, Combining classifiers: A theoretical framework, Pattern Anal. Appl., vol. 1, no. 1, pp. 18–27, 1998.
L. K. Hansen and P. Salamon, Neural network ensembles, IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 10, pp. 993–1001, 1990.
B. Knutson, Facial expressions of emotion influence interpersonal trait inferences, J. Nonverbal Behav., vol. 20, no. 3, pp. 165–182, 1996.
Z. Wang, X. He, and F. Liu, Examining the effect of smile intensity on age perceptions, Psychol. Rep., vol. 117, no. 1, pp. 188–205, 2015.
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